The Study Of Remote-Sensing Satellite Microwave Observation Data Assimilation Over Land

Owing to its wide coverage and high observation density,remote sensing satellite microwave observation data has become the most data used in numerical weather prediction system.However,most of the data collected from remote sensing satellites are the observations of higher-channels or data observed over sea.Due to the influence of clouds and precipitation,and the uncertainty of the surface emissivity,a large number of these observations are discarded,so the precondition of the assimilation of remote-sensing satellite microwave observation data over land is the calculation of complex surface emissivity.Based on the WRF model system,this paper analyzes the key technologies of assimilating remote sensing satellites observation over land,the inversion methods of surface emissivity,the access of atlas in RTTOV and the bias correction technology of AMSUA / MHS instruments,thus the application of AMSUA / MHS observation data over land in the WRFDA assimilation system is realized.Finally,the assimilation prediction experiment is designed for a specific typhoon case ”Matmo” to test the effect of AMSUA observation data over land on data assimilation and numerical prediction.The main results and conclusions of this paper are as follows:(1)The method of retrieving the surface emissivity using satellite observations and the access of the atlas in RTTOV are studied.The latest global average monthly surface emissivity is validated in the RTTOV and WRF systems,and the changes of surface emissivity over time and spaces are analyzed.(2)Based on the characteristics of AMSUA/MHS observations,the key technologies of AMSUA/MHS observation data assimilation are studied,and the application of AMSUA/MHS observation data over land to WRFDA system is realized.(3)Based on the data assimilation and numerical prediction experiment of Typhoon "Matmo",the temperature,relative humidity and the typhoon path are analyzed.The results show that the AMSUA observation data over land can influence the temperature and relative humidity of the assimilation result and produce positive effects,and the effect can be improved after adding the surface emissivity.Using the AMSUA observations over land and the surface emissivity,the prediction of the typhoon track can be better.The addition of the surface emissivity can improve the accuracy of the AMSUA data on the typhoon track forecasting,but the simulated result of the typhoon center pressure is not significantly improved.